LIMO (Lidar-Monocular) SLAM [1]} uses depth information from LiDAR to fit local planes to obtain depth information for features detected in the camera images. Moreover, semantic information is included.
Shin et al. [2]} combined a direct visual SLAM approach with sparse depth data from LiDARs. They used a sliding window-based optimization and included loop closure functionality. Robust SLAM results were obtained on different large-scale datasets.
